Model Selection in Time Series Analysis

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Explores model choice, prediction, and forecasting techniques in time series analysis.

Covers the analysis and modeling of univariate time series, focusing on stationarity, ARMA processes, and forecasting.

Explores ARMA models in time series analysis, covering model selection, forecasting, and precision assessment.

Explores multivariate time series analysis, cointegration, forecasting with ARMA models, and practical applications in interest rates analysis.

Explores forecasting methods and long memory in time series analysis.

Explores Time Series, covering model specification, diagnostics, and forecasting methods.

Covers residuals, diagnostics, overfitting, and forecasting methods in time series analysis.

Explores demand forecasting methods, time series analysis, trend forecasting, and the application of the Holt-Winter model.

Explores parametric estimation, integrated processes, seasonal modeling, and ARIMA model building in time series analysis.

Covers count data models and Poisson regression, then transitions to univariate time series analysis for forecasting economic variables.